--------------------------------------------------------------------------------------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  C:\Users\ralstonr\OneDrive - University of Birmingham\Work with Ron\Crossnational Main\Do Soldiers Get a Say.log
  log type:  text
 opened on:   8 Oct 2024, 09:24:05

. do "C:\Users\ralstonr\OneDrive - University of Birmingham\Work with Ron\Crossnational Main\Crossnational Do File_PoP.do"

. /// Do Soldiers Get a Say? ///
> /// Krebs, Ralston, Balzacq, Blagden, Rapport, Shenhav ///
> 
. 
. 
. 
. ********************************************************************************
. /// Table 1: Respondent Belief in Soldier Support for Military Operation  & 
> /// DV Respondent Support for Military Operation ///
> ********************************************************************************
. 
. * France 
. use "C:\Users\ralstonr\OneDrive - University of Birmingham\Work with Ron\Crossnational Main\France.dta"

. 
. reg favor soldierapproval citizen patriot employee desp

      Source |       SS           df       MS      Number of obs   =     1,089
-------------+----------------------------------   F(5, 1083)      =     11.74
       Model |  64.3819363         5  12.8763873   Prob > F        =    0.0000
    Residual |  1187.49869     1,083  1.09649002   R-squared       =    0.0514
-------------+----------------------------------   Adj R-squared   =    0.0470
       Total |  1251.88062     1,088  1.15062557   Root MSE        =    1.0471

---------------------------------------------------------------------------------
          favor | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
soldierapproval |   .9379463   .1334218     7.03   0.000     .6761518    1.199741
        citizen |   .1013777   .1004447     1.01   0.313    -.0957104    .2984659
        patriot |    .113421   .1000063     1.13   0.257    -.0828071     .309649
       employee |   -.051426    .101258    -0.51   0.612      -.25011     .147258
           desp |   .1609412   .1004196     1.60   0.109    -.0360978    .3579801
          _cons |   3.579365   .1064697    33.62   0.000     3.370454    3.788275
---------------------------------------------------------------------------------

. estimates store m1, title(Model 1)

. reg favor soldierapproval citizen patriot employee desp prioremp priorpat priorcit ideo6 ///
> rwa sdo bp miltherm hawk age edu income household selfserv female white

      Source |       SS           df       MS      Number of obs   =     1,089
-------------+----------------------------------   F(21, 1067)     =     10.83
       Model |  219.886833        21  10.4708016   Prob > F        =    0.0000
    Residual |  1031.99379     1,067  .967191932   R-squared       =    0.1756
-------------+----------------------------------   Adj R-squared   =    0.1594
       Total |  1251.88062     1,088  1.15062557   Root MSE        =    .98346

---------------------------------------------------------------------------------
          favor | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
soldierapproval |   .8073904   .1276506     6.33   0.000     .5569158    1.057865
        citizen |   .1621869   .0951764     1.70   0.089    -.0245672    .3489411
        patriot |   .1721721   .0946721     1.82   0.069    -.0135925    .3579367
       employee |  -.0183561   .0955057    -0.19   0.848    -.2057563    .1690441
           desp |   .1840917   .0950155     1.94   0.053    -.0023467    .3705301
       prioremp |   .1043666   .0985717     1.06   0.290    -.0890498     .297783
       priorpat |   .2513435   .0965974     2.60   0.009     .0618011    .4408858
       priorcit |   .2190465    .098991     2.21   0.027     .0248073    .4132856
          ideo6 |   .1373449    .118225     1.16   0.246    -.0946349    .3693248
            rwa |   -.231205   .2297432    -1.01   0.314    -.6820049    .2195948
            sdo |   .0765598   .1737983     0.44   0.660    -.2644655     .417585
             bp |   .7758139   .1673511     4.64   0.000     .4474392    1.104189
       miltherm |   .9127486    .158882     5.74   0.000      .600992    1.224505
           hawk |   .3655889   .1228627     2.98   0.003      .124509    .6066688
            age |  -.1674746   .1278629    -1.31   0.191    -.4183659    .0834166
            edu |    .036787   .1195418     0.31   0.758    -.1977767    .2713507
         income |  -.1117886    .242083    -0.46   0.644    -.5868014    .3632243
      household |    .058061   .0672194     0.86   0.388    -.0738363    .1899582
       selfserv |   .2011472   .0904201     2.22   0.026     .0237258    .3785686
         female |   .0193797   .0674124     0.29   0.774    -.1128961    .1516555
          white |  -.1688359    .116789    -1.45   0.149     -.397998    .0603262
          _cons |   2.442821    .218537    11.18   0.000      2.01401    2.871632
---------------------------------------------------------------------------------

. estimates store m2, title(Model 1)

. 
. * Israel
. use "C:\Users\ralstonr\OneDrive - University of Birmingham\Work with Ron\Crossnational Main\Israel.dta"

. 
. reg favor soldierapproval citizen employee 

      Source |       SS           df       MS      Number of obs   =     1,624
-------------+----------------------------------   F(3, 1620)      =     47.84
       Model |  158.327694         3  52.7758981   Prob > F        =    0.0000
    Residual |   1786.9728     1,620  1.10306963   R-squared       =    0.0814
-------------+----------------------------------   Adj R-squared   =    0.0797
       Total |  1945.30049     1,623  1.19858317   Root MSE        =    1.0503

---------------------------------------------------------------------------------
          favor | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
soldierapproval |   1.484893   .1275202    11.64   0.000     1.234771    1.735015
        citizen |   .0334725   .0639528     0.52   0.601    -.0919664    .1589113
       employee |   .0144189   .0647312     0.22   0.824    -.1125467    .1413846
          _cons |   4.587788   .1098551    41.76   0.000     4.372315    4.803261
---------------------------------------------------------------------------------

. estimates store m3, title(Model 1)

. reg favor soldierapproval citizen employee joinpat joincit ideology rwa sdo bp IDFtherm hawk  age  edu income selfserv female religiosity ib5.ethnicity

      Source |       SS           df       MS      Number of obs   =     1,506
-------------+----------------------------------   F(21, 1484)     =     28.44
       Model |  490.432759        21  23.3539409   Prob > F        =    0.0000
    Residual |  1218.80761     1,484   .82129893   R-squared       =    0.2869
-------------+----------------------------------   Adj R-squared   =    0.2768
       Total |  1709.24037     1,505  1.13570789   Root MSE        =    .90626

---------------------------------------------------------------------------------
          favor | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
soldierapproval |   1.011154   .1233649     8.20   0.000     .7691654    1.253142
        citizen |   .1317697   .0577649     2.28   0.023     .0184601    .2450792
       employee |  -.0543545   .0586234    -0.93   0.354     -.169348     .060639
        joinpat |   .0910894   .0544016     1.67   0.094    -.0156228    .1978015
        joincit |   .1454685   .0730086     1.99   0.047     .0022575    .2886795
       ideology |   .4600256    .108744     4.23   0.000     .2467173     .673334
            rwa |   .2272501   .1839127     1.24   0.217    -.1335063    .5880065
            sdo |  -.5146577   .1813723    -2.84   0.005    -.8704311   -.1588843
             bp |   1.875335   .2285498     8.21   0.000      1.42702     2.32365
       IDFtherm |   .5421484   .1382455     3.92   0.000     .2709711    .8133258
           hawk |   .4611926   .1038951     4.44   0.000     .2573958    .6649894
            age |   .1965609   .0897495     2.19   0.029     .0205115    .3726104
            edu |   .1193962   .0986964     1.21   0.227     -.074203    .3129955
         income |   .0853755   .0989466     0.86   0.388    -.1087146    .2794657
       selfserv |   .0381146   .0766715     0.50   0.619    -.1122814    .1885107
         female |  -.1777626   .0489115    -3.63   0.000    -.2737056   -.0818196
    religiosity |  -.1149598   .0895103    -1.28   0.199    -.2905399    .0606203
                |
      ethnicity |
             1  |  -.0888711   .0861722    -1.03   0.303    -.2579034    .0801611
             2  |   .0066558   .0931876     0.07   0.943    -.1761377    .1894493
             3  |   .0070873   .0967686     0.07   0.942    -.1827304    .1969051
             4  |    .193358    .101707     1.90   0.057    -.0061468    .3928627
                |
          _cons |   2.214002   .2363186     9.37   0.000     1.750448    2.677556
---------------------------------------------------------------------------------

. estimates store m4, title(Model 1)

. 
. 
. * UK
. use "C:\Users\ralstonr\OneDrive - University of Birmingham\Work with Ron\Crossnational Main\UK.dta"

. 
. reg favor soldierapproval patriot citizen employee desperate

      Source |       SS           df       MS      Number of obs   =     2,448
-------------+----------------------------------   F(5, 2442)      =     15.36
       Model |  121.035048         5  24.2070095   Prob > F        =    0.0000
    Residual |  3849.31136     2,442  1.57629458   R-squared       =    0.0305
-------------+----------------------------------   Adj R-squared   =    0.0285
       Total |  3970.34641     2,447  1.62253633   Root MSE        =    1.2555

---------------------------------------------------------------------------------
          favor | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
soldierapproval |   .9536712   .1197932     7.96   0.000     .7187643    1.188578
        patriot |   -.035131   .0780133    -0.45   0.653    -.1881101    .1178482
        citizen |  -.2551906   .0773958    -3.30   0.001    -.4069589   -.1034223
       employee |  -.0319908   .0776969    -0.41   0.681    -.1843493    .1203678
      desperate |  -.0846781   .0781588    -1.08   0.279    -.2379425    .0685862
          _cons |   3.668497   .0804871    45.58   0.000     3.510667    3.826327
---------------------------------------------------------------------------------

. estimates store m5, title(Model 1)

. reg favor soldierapproval patriot citizen employee desperate joinemp joinpat joincit ideo6  rwa sdo bp miltherm hawk  age  edu income selfserv household female white

      Source |       SS           df       MS      Number of obs   =     2,448
-------------+----------------------------------   F(21, 2426)     =     22.31
       Model |  642.597863        21  30.5998982   Prob > F        =    0.0000
    Residual |  3327.74854     2,426  1.37170179   R-squared       =    0.1618
-------------+----------------------------------   Adj R-squared   =    0.1546
       Total |  3970.34641     2,447  1.62253633   Root MSE        =    1.1712

---------------------------------------------------------------------------------
          favor | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
soldierapproval |   .8015676   .1132466     7.08   0.000     .5794975    1.023638
        patriot |  -.0092645   .0729848    -0.13   0.899    -.1523835    .1338545
        citizen |  -.2010715   .0723318    -2.78   0.005    -.3429099   -.0592331
       employee |   .0000629   .0727224     0.00   0.999    -.1425415    .1426673
      desperate |  -.0981404   .0732136    -1.34   0.180    -.2417082    .0454273
        joinemp |   .1595585   .0775474     2.06   0.040     .0074925    .3116245
        joinpat |   .1146881   .0870332     1.32   0.188     -.055979    .2853551
        joincit |   .2297938   .0986617     2.33   0.020     .0363239    .4232637
          ideo6 |   .2794197   .0954026     2.93   0.003     .0923407    .4664988
            rwa |   .2441077   .1822105     1.34   0.180    -.1131965    .6014119
            sdo |   .3112913   .1782748     1.75   0.081    -.0382952    .6608778
             bp |   .3571971   .1355347     2.64   0.008     .0914214    .6229728
       miltherm |   1.206446   .1217657     9.91   0.000      .967671    1.445222
           hawk |    .631614   .1087913     5.81   0.000     .4182805    .8449475
            age |   .1080504   .0843284     1.28   0.200    -.0573127    .2734136
            edu |   .0459131   .0742156     0.62   0.536    -.0996195    .1914456
         income |   .2244024   .1135583     1.98   0.048      .001721    .4470837
       selfserv |  -.2518735       .113    -2.23   0.026      -.47346    -.030287
      household |   .0470554   .0635584     0.74   0.459     -.077579    .1716898
         female |  -.2113003   .0499624    -4.23   0.000    -.3092737    -.113327
          white |  -.0348824   .0798126    -0.44   0.662    -.1913903    .1216255
          _cons |   1.889334   .1696231    11.14   0.000     1.556713    2.221955
---------------------------------------------------------------------------------

. estimates store m6, title(Model 1)

. 
. 
. * USA
. use "C:\Users\ralstonr\OneDrive - University of Birmingham\Work with Ron\Crossnational Main\US.dta"

. 
. reg favor soldierapproval patriot citizen employee desperate

      Source |       SS           df       MS      Number of obs   =     2,451
-------------+----------------------------------   F(5, 2445)      =     25.08
       Model |  231.129998         5  46.2259996   Prob > F        =    0.0000
    Residual |  4507.16458     2,445  1.84342109   R-squared       =    0.0488
-------------+----------------------------------   Adj R-squared   =    0.0468
       Total |  4738.29457     2,450  1.93399779   Root MSE        =    1.3577

---------------------------------------------------------------------------------
          favor | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
soldierapproval |   1.165015   .1087946    10.71   0.000     .9516755    1.378354
        patriot |   .0552559   .0859951     0.64   0.521    -.1133748    .2238867
        citizen |   .0615943    .084999     0.72   0.469    -.1050831    .2282717
       employee |   .0864054   .0829989     1.04   0.298      -.07635    .2491609
      desperate |   .0576549   .0836628     0.69   0.491    -.1064023    .2217122
          _cons |   3.770834   .0787906    47.86   0.000      3.61633    3.925337
---------------------------------------------------------------------------------

. estimates store m7, title(Model 1)

. reg favor soldierapproval patriot citizen employee desperate joinemp joinpat joincit n_ideo ///
>  n_rwa n_sdo n_bp n_miltherm n_hawk  n_age n_edu n_income household selfserv female nonwhite

      Source |       SS           df       MS      Number of obs   =     2,451
-------------+----------------------------------   F(21, 2429)     =     23.09
       Model |  788.544693        21  37.5497473   Prob > F        =    0.0000
    Residual |  3949.74988     2,429  1.62608064   R-squared       =    0.1664
-------------+----------------------------------   Adj R-squared   =    0.1592
       Total |  4738.29457     2,450  1.93399779   Root MSE        =    1.2752

---------------------------------------------------------------------------------
          favor | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
soldierapproval |   .8747443   .1043002     8.39   0.000     .6702177    1.079271
        patriot |   .0265682    .081038     0.33   0.743    -.1323426     .185479
        citizen |   .0828452   .0799728     1.04   0.300    -.0739768    .2396671
       employee |   .0546852   .0782833     0.70   0.485    -.0988237     .208194
      desperate |   .0071941   .0788382     0.09   0.927    -.1474029    .1617912
        joinemp |   .4526124   .0922743     4.91   0.000     .2716679    .6335568
        joinpat |   .4006153   .0979226     4.09   0.000     .2085949    .5926358
        joincit |    .353936   .1095072     3.23   0.001     .1391988    .5686731
         n_ideo |   .1611615   .1096864     1.47   0.142    -.0539272    .3762502
          n_rwa |   .4841214   .1617631     2.99   0.003     .1669135    .8013294
          n_sdo |  -.6906206   .1680108    -4.11   0.000     -1.02008   -.3611613
           n_bp |   .8009805   .1344201     5.96   0.000     .5373906     1.06457
     n_miltherm |   .8159405   .1155111     7.06   0.000     .5894299    1.042451
         n_hawk |   .3930681   .1138363     3.45   0.001     .1698418    .6162944
          n_age |   .0853187   .0892274     0.96   0.339     -.089651    .2602885
          n_edu |   .0173336   .1209697     0.14   0.886    -.2198808    .2545481
       n_income |   .0466823    .125802     0.37   0.711    -.2000081    .2933726
      household |   .0493348   .0613033     0.80   0.421    -.0708774     .169547
       selfserv |   .0260703   .0929667     0.28   0.779     -.156232    .2083725
         female |  -.1435316   .0550138    -2.61   0.009    -.2514104   -.0356528
       nonwhite |  -.2127243   .0608924    -3.49   0.000    -.3321307   -.0933179
          _cons |   2.455182    .150994    16.26   0.000     2.159091    2.751272
---------------------------------------------------------------------------------

. estimates store m8, title(Model 1)

. 
. esttab m1 m2 m3 m4 m5 m6 m7 m8 using "DoSoldiersGetASay_Table 1.rtf", se r2  replace starlevels(+ 0.10 * 0.05 ** 0.01 *** 0.0001) b(2) se(2)    
(file DoSoldiersGetASay_Table 1.rtf not found)
(output written to DoSoldiersGetASay_Table 1.rtf)

. 
. coefplot m2 m4 m6 m8, scheme(s1mono) mlcolor(black) mfcolor(none) mcolor(black) ///
>                 xline(0, lpattern(dash) lcolor(red%50))  ///
>                 drop(_cons) mlabposition(6)  ///
>                 aspect(1) xlab(-1 "Less Favorable"  0  1 "More Favorable")

. 
. 
. ******************************************************************************** 
. /// Table 2: Respondent Belief in Soldier Support for Military Operation & 
> /// DV Respondent Evaluation of Likely Battlefield Performance ///
> ********************************************************************************
. 
. * France 
. use "C:\Users\ralstonr\OneDrive - University of Birmingham\Work with Ron\Crossnational Main\France.dta"

. 
. reg soldierbattle soldierapproval citizen patriot employee desp

      Source |       SS           df       MS      Number of obs   =     1,089
-------------+----------------------------------   F(5, 1083)      =     14.21
       Model |  39.9028824         5  7.98057649   Prob > F        =    0.0000
    Residual |  608.021819     1,083  .561423656   R-squared       =    0.0616
-------------+----------------------------------   Adj R-squared   =    0.0573
       Total |  647.924702     1,088  .595519027   Root MSE        =    .74928

---------------------------------------------------------------------------------
  soldierbattle | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
soldierapproval |   .7541962   .0954706     7.90   0.000     .5668678    .9415245
        citizen |   .0767574   .0718737     1.07   0.286      -.06427    .2177848
        patriot |   .0712765     .07156     1.00   0.319    -.0691355    .2116884
       employee |    -.00013   .0724556    -0.00   0.999    -.1422993    .1420393
           desp |   .1548256   .0718557     2.15   0.031     .0138334    .2958178
          _cons |   2.711665   .0761849    35.59   0.000     2.562179    2.861152
---------------------------------------------------------------------------------

. estimates store m1a, title(Model 1)

. reg soldierbattle soldierapproval citizen patriot employee desp prioremp priorpat priorcit ideo6 ///
>   rwa sdo bp miltherm hawk age edu income household selfserv female white

      Source |       SS           df       MS      Number of obs   =     1,089
-------------+----------------------------------   F(21, 1067)     =      7.76
       Model |  85.8218254        21  4.08675359   Prob > F        =    0.0000
    Residual |  562.102876     1,067  .526806819   R-squared       =    0.1325
-------------+----------------------------------   Adj R-squared   =    0.1154
       Total |  647.924702     1,088  .595519027   Root MSE        =    .72581

---------------------------------------------------------------------------------
  soldierbattle | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
soldierapproval |   .6405164   .0942089     6.80   0.000     .4556606    .8253722
        citizen |   .0983566   .0702423     1.40   0.162    -.0394721    .2361853
        patriot |   .0980969   .0698701     1.40   0.161    -.0390015    .2351952
       employee |   .0105213   .0704853     0.15   0.881    -.1277842    .1488268
           desp |   .1635485   .0701235     2.33   0.020     .0259529    .3011442
       prioremp |   .2065266   .0727481     2.84   0.005      .063781    .3492721
       priorpat |   .1695817    .071291     2.38   0.018     .0296952    .3094681
       priorcit |   .1851274   .0730576     2.53   0.011     .0417746    .3284802
          ideo6 |  -.0277674   .0872526    -0.32   0.750    -.1989736    .1434389
            rwa |  -.0089154   .1695556    -0.05   0.958    -.3416156    .3237849
            sdo |  -.2673749    .128267    -2.08   0.037    -.5190591   -.0156908
             bp |   .3893648   .1235088     3.15   0.002     .1470171    .6317125
       miltherm |   .6079642   .1172584     5.18   0.000      .377881    .8380475
           hawk |   .1333934   .0906754     1.47   0.142    -.0445289    .3113157
            age |  -.0108001   .0943656    -0.11   0.909    -.1959634    .1743632
            edu |   .1641896   .0882245     1.86   0.063    -.0089236    .3373028
         income |  -.0508912   .1786626    -0.28   0.776    -.4014612    .2996787
      household |   .0141188   .0496094     0.28   0.776    -.0832243    .1114619
       selfserv |   .0800084    .066732     1.20   0.231    -.0509325    .2109493
         female |   .0048606   .0497518     0.10   0.922    -.0927619    .1024831
          white |   .0683237   .0861928     0.79   0.428     -.100803    .2374504
          _cons |   1.938188   .1612852    12.02   0.000     1.621716     2.25466
---------------------------------------------------------------------------------

. estimates store m2a, title(Model 1)

. 
. * Israel
. 
. use "C:\Users\ralstonr\OneDrive - University of Birmingham\Work with Ron\Crossnational Main\Israel.dta"

. 
. reg soldierbattle soldierapproval citizen employee 

      Source |       SS           df       MS      Number of obs   =     1,624
-------------+----------------------------------   F(3, 1620)      =    127.05
       Model |  375.397637         3  125.132546   Prob > F        =    0.0000
    Residual |  1595.52786     1,620  .984893738   R-squared       =    0.1905
-------------+----------------------------------   Adj R-squared   =    0.1890
       Total |  1970.92549     1,623  1.21437184   Root MSE        =    .99242

---------------------------------------------------------------------------------
  soldierbattle | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
soldierapproval |   1.720613   .1204959    14.28   0.000     1.484269    1.956958
        citizen |   .0645849     .06043     1.07   0.285    -.0539443    .1831141
       employee |  -.4921328   .0611655    -8.05   0.000    -.6121047   -.3721609
          _cons |   4.691592   .1038038    45.20   0.000     4.487989    4.895196
---------------------------------------------------------------------------------

. estimates store m3a, title(Model 1)

. reg soldierbattle soldierapproval citizen employee joinpat joincit ideology   rwa sdo bp IDFtherm hawk  age  edu income selfserv female religiosity ib5.ethnicity

      Source |       SS           df       MS      Number of obs   =     1,506
-------------+----------------------------------   F(21, 1484)     =     31.21
       Model |  527.407667        21  25.1146508   Prob > F        =    0.0000
    Residual |  1194.04851     1,484  .804614898   R-squared       =    0.3064
-------------+----------------------------------   Adj R-squared   =    0.2966
       Total |  1721.45618     1,505   1.1438247   Root MSE        =      .897

---------------------------------------------------------------------------------
  soldierbattle | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
soldierapproval |   1.445152   .1221055    11.84   0.000     1.205634     1.68467
        citizen |   .1271746   .0571752     2.22   0.026     .0150218    .2393273
       employee |  -.4865508   .0580249    -8.39   0.000    -.6003703   -.3727313
        joinpat |   .1390888   .0538462     2.58   0.010     .0334661    .2447115
        joincit |   .1056919   .0722632     1.46   0.144     -.036057    .2474408
       ideology |   .1510887   .1076338     1.40   0.161     -.060042    .3622193
            rwa |   .4573905   .1820351     2.51   0.012     .1003171    .8144639
            sdo |  -.6413583   .1795207    -3.57   0.000    -.9934996   -.2892171
             bp |   .4695984   .2262165     2.08   0.038     .0258604    .9133364
       IDFtherm |   1.009065   .1368341     7.37   0.000     .7406557    1.277473
           hawk |  -.0357274   .1028344    -0.35   0.728    -.2374435    .1659888
            age |   .4393369   .0888333     4.95   0.000     .2650848     .613589
            edu |  -.0514126   .0976888    -0.53   0.599    -.2430354    .1402101
         income |  -.0446014   .0979365    -0.46   0.649      -.23671    .1475072
       selfserv |  -.0704777   .0758888    -0.93   0.353    -.2193384    .0783829
         female |   .0909703   .0484121     1.88   0.060    -.0039932    .1859338
    religiosity |  -.1437383   .0885964    -1.62   0.105    -.3175259    .0300493
                |
      ethnicity |
             1  |  -.0322302   .0852924    -0.38   0.706    -.1995367    .1350764
             2  |  -.0533433   .0922363    -0.58   0.563    -.2342706    .1275841
             3  |  -.0126395   .0957806    -0.13   0.895    -.2005194    .1752403
             4  |   .1101813   .1006686     1.09   0.274    -.0872867    .3076493
                |
          _cons |   3.378225    .233906    14.44   0.000     2.919404    3.837047
---------------------------------------------------------------------------------

. estimates store m4a, title(Model 1)

. 
. 
. * UK
. 
. use "C:\Users\ralstonr\OneDrive - University of Birmingham\Work with Ron\Crossnational Main\UK.dta"

. 
. reg soldierbattle soldierapproval patriot citizen employee desperate

      Source |       SS           df       MS      Number of obs   =     2,448
-------------+----------------------------------   F(5, 2442)      =     17.00
       Model |  53.0088881         5  10.6017776   Prob > F        =    0.0000
    Residual |  1522.82771     2,442  .623598572   R-squared       =    0.0336
-------------+----------------------------------   Adj R-squared   =    0.0317
       Total |   1575.8366     2,447  .643987168   Root MSE        =    .78968

---------------------------------------------------------------------------------
  soldierbattle | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
soldierapproval |   .4694565    .075347     6.23   0.000     .3217058    .6172072
        patriot |   .1825863   .0490685     3.72   0.000     .0863662    .2788065
        citizen |   .0679609   .0486801     1.40   0.163    -.0274977    .1634195
       employee |  -.1407806   .0488694    -2.88   0.004    -.2366105   -.0449508
      desperate |  -.0332859     .04916    -0.68   0.498    -.1296854    .0631137
          _cons |   3.423039   .0506244    67.62   0.000     3.323768    3.522311
---------------------------------------------------------------------------------

. estimates store m5a, title(Model 1)

. reg soldierbattle soldierapproval patriot citizen employee desperate joinemp joinpat joincit ideo6   rwa sdo bp miltherm hawk  age  edu income selfserv household female
>  white

      Source |       SS           df       MS      Number of obs   =     2,448
-------------+----------------------------------   F(21, 2426)     =     21.21
       Model |  244.411726        21  11.6386536   Prob > F        =    0.0000
    Residual |  1331.42488     2,426   .54881487   R-squared       =    0.1551
-------------+----------------------------------   Adj R-squared   =    0.1478
       Total |   1575.8366     2,447  .643987168   Root MSE        =    .74082

---------------------------------------------------------------------------------
  soldierbattle | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
soldierapproval |   .4170856   .0716322     5.82   0.000      .276619    .5575522
        patriot |   .1941848   .0461653     4.21   0.000     .1036573    .2847123
        citizen |   .0856963   .0457522     1.87   0.061    -.0040212    .1754137
       employee |  -.1254927   .0459993    -2.73   0.006    -.2156946   -.0352907
      desperate |  -.0527533     .04631    -1.14   0.255    -.1435646     .038058
        joinemp |   .1191395   .0490513     2.43   0.015     .0229527    .2153262
        joinpat |   .1004204   .0550513     1.82   0.068    -.0075321    .2083729
        joincit |   .1117213   .0624068     1.79   0.074    -.0106548    .2340973
          ideo6 |   .0193319   .0603453     0.32   0.749    -.0990017    .1376656
            rwa |   .5502039   .1152541     4.77   0.000     .3241972    .7762105
            sdo |   .0768583   .1127646     0.68   0.496    -.1442666    .2979833
             bp |  -.0194807   .0857301    -0.23   0.820    -.1875926    .1486311
       miltherm |   .8204884   .0770208    10.65   0.000      .669455    .9715217
           hawk |  -.2037558   .0688141    -2.96   0.003    -.3386962   -.0688154
            age |   .2849522   .0533405     5.34   0.000     .1803546    .3895498
            edu |  -.0284867   .0469438    -0.61   0.544    -.1205408    .0635674
         income |  -.0690092   .0718294    -0.96   0.337    -.2098624    .0718441
       selfserv |  -.0922073   .0714762    -1.29   0.197     -.232368    .0479535
      household |   .0564747   .0402028     1.40   0.160    -.0223606    .1353101
         female |   .0229482   .0316029     0.73   0.468    -.0390232    .0849196
          white |   .1147357   .0504841     2.27   0.023     .0157393    .2137321
          _cons |   2.225201   .1072922    20.74   0.000     2.014807    2.435595
---------------------------------------------------------------------------------

. estimates store m6a, title(Model 1)

. 
. 
. esttab m1a m2a m3a m4a m5a m6a  using "DoSoldiersGetASay_Table 2.rtf", se r2  replace starlevels(+ 0.10 * 0.05 ** 0.01 *** 0.0001) b(2) se(2)
(file DoSoldiersGetASay_Table 2.rtf not found)
(output written to DoSoldiersGetASay_Table 2.rtf)

. 
. 
. ********************************************************************************
. /// Table 3: Respondent Empathy & DV Respondent Support for Military Operation & 
> /// DV Respondent Belief in Soldier Support for Military Operation ///
> ********************************************************************************
. 
. * France 
. use "C:\Users\ralstonr\OneDrive - University of Birmingham\Work with Ron\Crossnational Main\France.dta"

. 
. 
. reg favor c.concern##extrinsic soldierapproval  prioremp priorpat priorcit ideo6 ///
>  rwa sdo bp miltherm hawk age edu income household selfserv female white if control==0 

      Source |       SS           df       MS      Number of obs   =       871
-------------+----------------------------------   F(20, 850)      =     10.43
       Model |  196.298497        20  9.81492485   Prob > F        =    0.0000
    Residual |   799.63032       850  .940741554   R-squared       =    0.1971
-------------+----------------------------------   Adj R-squared   =    0.1782
       Total |  995.928817       870  1.14474577   Root MSE        =    .96992

-------------------------------------------------------------------------------------
              favor | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
            concern |   .3078573   .2734427     1.13   0.261    -.2288447    .8445593
        1.extrinsic |   .1685908   .2269171     0.74   0.458    -.2767928    .6139744
                    |
extrinsic#c.concern |
                 1  |  -.4046796   .3454946    -1.17   0.242    -1.082802    .2734429
                    |
    soldierapproval |   .7652271   .1402582     5.46   0.000      .489934     1.04052
           prioremp |   .0947119   .1108511     0.85   0.393     -.122862    .3122859
           priorpat |   .2107134   .1072094     1.97   0.050     .0002872    .4211396
           priorcit |   .2488267   .1091398     2.28   0.023     .0346115    .4630418
              ideo6 |   .1613415   .1339294     1.20   0.229    -.1015297    .4242126
                rwa |  -.1633021   .2553131    -0.64   0.523    -.6644201    .3378159
                sdo |   .0480049    .208108     0.23   0.818    -.3604609    .4564707
                 bp |   .8610539   .1850526     4.65   0.000     .4978402    1.224268
           miltherm |    1.03714   .1757922     5.90   0.000      .692102    1.382177
               hawk |   .3356276   .1409618     2.38   0.017     .0589535    .6123017
                age |  -.2268106    .144344    -1.57   0.116     -.510123    .0565017
                edu |   .0600172    .131968     0.45   0.649    -.1990041    .3190386
             income |   -.113641   .2714399    -0.42   0.676     -.646412      .41913
          household |   .0892862   .0742681     1.20   0.230    -.0564841    .2350566
           selfserv |   .1747561   .1024139     1.71   0.088    -.0262576    .3757698
             female |   .0042116   .0765125     0.06   0.956    -.1459639    .1543872
              white |  -.2777714   .1287798    -2.16   0.031    -.5305351   -.0250076
              _cons |   2.410899    .293633     8.21   0.000     1.834568     2.98723
-------------------------------------------------------------------------------------

. estimates store m1d, title(Model 1)

. reg favor c.persp##extrinsic soldierapproval  prioremp priorpat priorcit ideo6 ///
> rwa sdo bp miltherm hawk age edu income household selfserv female white if control==0 

      Source |       SS           df       MS      Number of obs   =       871
-------------+----------------------------------   F(20, 850)      =     10.44
       Model |  196.466546        20  9.82332728   Prob > F        =    0.0000
    Residual |  799.462272       850  .940543849   R-squared       =    0.1973
-------------+----------------------------------   Adj R-squared   =    0.1784
       Total |  995.928817       870  1.14474577   Root MSE        =    .96982

-----------------------------------------------------------------------------------
            favor | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
------------------+----------------------------------------------------------------
            persp |   .3383414   .3342612     1.01   0.312    -.3177328    .9944155
      1.extrinsic |  -.0825637   .2910233    -0.28   0.777    -.6537723    .4886448
                  |
extrinsic#c.persp |
               1  |   -.007077   .4763797    -0.01   0.988    -.9420955    .9279414
                  |
  soldierapproval |   .7664782   .1402584     5.46   0.000     .4911848    1.041772
         prioremp |   .0858169   .1110472     0.77   0.440     -.132142    .3037757
         priorpat |   .2039769   .1072442     1.90   0.058    -.0065176    .4144714
         priorcit |    .246478   .1092321     2.26   0.024     .0320818    .4608743
            ideo6 |   .1763533   .1331924     1.32   0.186    -.0850713     .437778
              rwa |  -.1527937   .2536206    -0.60   0.547    -.6505899    .3450024
              sdo |   .0568531   .1997894     0.28   0.776    -.3352854    .4489916
               bp |   .8162275   .1877843     4.35   0.000     .4476523    1.184803
         miltherm |   1.016104   .1757225     5.78   0.000     .6712028    1.361004
             hawk |   .3377901   .1395414     2.42   0.016      .063904    .6116761
              age |  -.2181216   .1431811    -1.52   0.128    -.4991516    .0629084
              edu |    .035694   .1326636     0.27   0.788    -.2246926    .2960806
           income |  -.1010343   .2712915    -0.37   0.710    -.6335141    .4314455
        household |   .0882422   .0743179     1.19   0.235    -.0576258    .2341103
         selfserv |   .1715233   .1024049     1.67   0.094    -.0294728    .3725194
           female |   .0025491   .0748951     0.03   0.973     -.144452    .1495501
            white |  -.2662251   .1288773    -2.07   0.039    -.5191801   -.0132701
            _cons |   2.419155   .3046805     7.94   0.000      1.82114    3.017169
-----------------------------------------------------------------------------------

. estimates store m2d, title(Model 1)

. 
. 
. reg soldierapproval c.concern##extrinsic   prioremp priorpat priorcit ideo6 ///
> rwa sdo bp miltherm hawk age edu income household selfserv female white if control==0 

      Source |       SS           df       MS      Number of obs   =       871
-------------+----------------------------------   F(19, 851)      =      3.66
       Model |  3.91248855        19   .20592045   Prob > F        =    0.0000
    Residual |  47.8204334       851  .056193224   R-squared       =    0.0756
-------------+----------------------------------   Adj R-squared   =    0.0550
       Total |  51.7329219       870  .059463129   Root MSE        =    .23705

-------------------------------------------------------------------------------------
    soldierapproval | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
            concern |   .1938789    .066499     2.92   0.004     .0633577    .3244001
        1.extrinsic |   .0822901   .0553875     1.49   0.138     -.026422    .1910022
                    |
extrinsic#c.concern |
                 1  |  -.2518304   .0839975    -3.00   0.003     -.416697   -.0869638
                    |
           prioremp |  -.0129338   .0270887    -0.48   0.633    -.0661023    .0402348
           priorpat |  -.0009824   .0262023    -0.04   0.970    -.0524111    .0504463
           priorcit |  -.0029089   .0266739    -0.11   0.913    -.0552633    .0494455
              ideo6 |   .0301332   .0327165     0.92   0.357    -.0340812    .0943476
                rwa |   .0674325   .0623565     1.08   0.280    -.0549581     .189823
                sdo |  -.0790182   .0507901    -1.56   0.120    -.1787067    .0206703
                 bp |   .1134754   .0450599     2.52   0.012     .0250339    .2019169
           miltherm |   .0566653   .0429202     1.32   0.187    -.0275767    .1409072
               hawk |  -.0297093   .0344365    -0.86   0.389    -.0972996    .0378811
                age |   .0248119   .0352679     0.70   0.482    -.0444103    .0940341
                edu |   .0487261   .0322101     1.51   0.131    -.0144945    .1119467
             income |   .0232447    .066336     0.35   0.726    -.1069566     .153446
          household |   .0136947   .0181453     0.75   0.451      -.02192    .0493095
           selfserv |  -.0266306   .0250136    -1.06   0.287    -.0757262     .022465
             female |  -.0363294   .0186584    -1.95   0.052    -.0729513    .0002924
              white |    .011211   .0314719     0.36   0.722    -.0505605    .0729826
              _cons |   .4123752   .0703588     5.86   0.000     .2742781    .5504724
-------------------------------------------------------------------------------------

. estimates store m3d, title(Model 1)

. reg soldierapproval c.persp##extrinsic   prioremp priorpat priorcit ideo6 ///
>  rwa sdo bp miltherm hawk age edu income household selfserv female white if control==0 

      Source |       SS           df       MS      Number of obs   =       871
-------------+----------------------------------   F(19, 851)      =      3.67
       Model |  3.92265204        19  .206455371   Prob > F        =    0.0000
    Residual |  47.8102699       851  .056181281   R-squared       =    0.0758
-------------+----------------------------------   Adj R-squared   =    0.0552
       Total |  51.7329219       870  .059463129   Root MSE        =    .23703

-----------------------------------------------------------------------------------
  soldierapproval | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
------------------+----------------------------------------------------------------
            persp |   .2591657   .0812099     3.19   0.001     .0997705    .4185609
      1.extrinsic |   .0326254   .0711181     0.46   0.647    -.1069621    .1722129
                  |
extrinsic#c.persp |
               1  |  -.1837363   .1162581    -1.58   0.114    -.4119225    .0444499
                  |
         prioremp |   -.019422   .0271321    -0.72   0.474    -.0726757    .0338316
         priorpat |  -.0044442   .0262104    -0.17   0.865    -.0558887    .0470003
         priorcit |  -.0024174   .0266965    -0.09   0.928    -.0548161    .0499813
            ideo6 |   .0366666   .0325283     1.13   0.260    -.0271786    .1005118
              rwa |   .0782205   .0619276     1.26   0.207    -.0433282    .1997692
              sdo |  -.0793082   .0487534    -1.63   0.104    -.1749992    .0163827
               bp |   .0923841   .0457856     2.02   0.044     .0025181      .18225
         miltherm |   .0433194   .0429214     1.01   0.313    -.0409248    .1275636
             hawk |  -.0322772   .0340864    -0.95   0.344    -.0991804     .034626
              age |   .0291972   .0349796     0.83   0.404    -.0394592    .0978535
              edu |   .0357413   .0324002     1.10   0.270    -.0278523     .099335
           income |   .0332807   .0662946     0.50   0.616    -.0968394    .1634008
        household |    .014296   .0181569     0.79   0.431    -.0213415    .0499336
         selfserv |  -.0296163   .0250074    -1.18   0.237    -.0786998    .0194672
           female |  -.0366655   .0182614    -2.01   0.045    -.0725081   -.0008229
            white |   .0173947   .0314923     0.55   0.581    -.0444171    .0792064
            _cons |   .3893111   .0732592     5.31   0.000     .2455213    .5331009
-----------------------------------------------------------------------------------

. estimates store m4d, title(Model 1)

. 
. * UK
. use "C:\Users\ralstonr\OneDrive - University of Birmingham\Work with Ron\Crossnational Main\UK.dta"

. 
. reg favor c.concern##extrinsic soldierapproval joinemp joinpat joincit ideo6  rwa sdo bp miltherm hawk  age  edu income selfserv household female white if control==0

      Source |       SS           df       MS      Number of obs   =     1,400
-------------+----------------------------------   F(20, 1379)     =     20.12
       Model |  485.695955        20  24.2847977   Prob > F        =    0.0000
    Residual |  1664.14333     1,379  1.20677544   R-squared       =    0.2259
-------------+----------------------------------   Adj R-squared   =    0.2147
       Total |  2149.83929     1,399  1.53669713   Root MSE        =    1.0985

-------------------------------------------------------------------------------------
              favor | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
            concern |   .4681752   .2385652     1.96   0.050     .0001853    .9361651
        1.extrinsic |    .513528   .2207488     2.33   0.020     .0804883    .9465677
                    |
extrinsic#c.concern |
                 1  |  -.7221148   .3248487    -2.22   0.026    -1.359366   -.0848638
                    |
    soldierapproval |     .70848   .1383983     5.12   0.000     .4369859    .9799741
            joinemp |   .3373112   .0986923     3.42   0.001     .1437079    .5309145
            joinpat |   .3647567    .110659     3.30   0.001     .1476786    .5818348
            joincit |   .4458666   .1257921     3.54   0.000     .1991021     .692631
              ideo6 |   .3901862   .1209881     3.22   0.001     .1528455    .6275269
                rwa |   .4187647   .2276797     1.84   0.066    -.0278714    .8654008
                sdo |   .2863411    .217291     1.32   0.188    -.1399156    .7125978
                 bp |   .2156271   .1687123     1.28   0.201    -.1153335    .5465877
           miltherm |   1.370505   .1540183     8.90   0.000     1.068369    1.672641
               hawk |   .8699773   .1405897     6.19   0.000     .5941844     1.14577
                age |   .1125349   .1045225     1.08   0.282    -.0925054    .3175752
                edu |   .0175671   .0923338     0.19   0.849    -.1635628     .198697
             income |   .1064188   .1404599     0.76   0.449    -.1691195     .381957
           selfserv |  -.3041152    .145202    -2.09   0.036    -.5889558   -.0192745
          household |   .0399366   .0772697     0.52   0.605    -.1116423    .1915155
             female |  -.1942828   .0640807    -3.03   0.002    -.3199889   -.0685767
              white |  -.0200562   .0984782    -0.20   0.839    -.2132395    .1731272
              _cons |   1.085855   .2592223     4.19   0.000     .5773425    1.594368
-------------------------------------------------------------------------------------

. estimates store m5d, title(Model 1)

. reg favor c.persp##extrinsic soldierapproval joinemp joinpat joincit ideo6  rwa sdo bp miltherm hawk  age  edu income selfserv household female white if control==0

      Source |       SS           df       MS      Number of obs   =     1,400
-------------+----------------------------------   F(20, 1379)     =     19.80
       Model |  479.649225        20  23.9824613   Prob > F        =    0.0000
    Residual |  1670.19006     1,379   1.2111603   R-squared       =    0.2231
-------------+----------------------------------   Adj R-squared   =    0.2118
       Total |  2149.83929     1,399  1.53669713   Root MSE        =    1.1005

-----------------------------------------------------------------------------------
            favor | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
------------------+----------------------------------------------------------------
            persp |  -.0489169   .2665574    -0.18   0.854    -.5718187     .473985
      1.extrinsic |   .1075947   .2451442     0.44   0.661    -.3733011    .5884906
                  |
extrinsic#c.persp |
               1  |  -.1064292   .3767933    -0.28   0.778    -.8455793    .6327209
                  |
  soldierapproval |   .7353158   .1384213     5.31   0.000     .4637767    1.006855
          joinemp |   .3278675    .098762     3.32   0.001     .1341274    .5216076
          joinpat |   .3606988   .1107234     3.26   0.001     .1434943    .5779033
          joincit |   .4433717   .1259695     3.52   0.000     .1962591    .6904844
            ideo6 |   .3734108   .1202014     3.11   0.002     .1376134    .6092082
              rwa |   .4208569   .2281437     1.84   0.065    -.0266893    .8684031
              sdo |   .3125639   .2178797     1.43   0.152    -.1148476    .7399753
               bp |   .2090229   .1693706     1.23   0.217     -.123229    .5412749
         miltherm |   1.379582   .1530616     9.01   0.000     1.079324    1.679841
             hawk |   .8291966   .1394002     5.95   0.000     .5557373    1.102656
              age |    .121096   .1044894     1.16   0.247    -.0838795    .3260714
              edu |   .0170211   .0926887     0.18   0.854    -.1648051    .1988472
           income |   .0962892   .1407007     0.68   0.494    -.1797215    .3722998
         selfserv |  -.2881656   .1454203    -1.98   0.048    -.5734345   -.0028967
        household |   .0392914   .0774386     0.51   0.612    -.1126187    .1912015
           female |  -.1814848   .0626066    -2.90   0.004    -.3042993   -.0586703
            white |  -.0305294     .09861    -0.31   0.757    -.2239712    .1629123
            _cons |   1.425834   .2634154     5.41   0.000     .9090956    1.942572
-----------------------------------------------------------------------------------

. estimates store m6d, title(Model 1)

. 
. reg soldierapproval c.concern##extrinsic  joinemp joinpat joincit ideo6  rwa sdo bp miltherm hawk  age  edu income selfserv household female white if control==0

      Source |       SS           df       MS      Number of obs   =     1,400
-------------+----------------------------------   F(19, 1380)     =      5.80
       Model |  5.03359583        19  .264926096   Prob > F        =    0.0000
    Residual |  63.0035024     1,380  .045654712   R-squared       =    0.0740
-------------+----------------------------------   Adj R-squared   =    0.0612
       Total |  68.0370982     1,399  .048632665   Root MSE        =    .21367

-------------------------------------------------------------------------------------
    soldierapproval | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
            concern |   .1609017   .0461994     3.48   0.001     .0702731    .2515303
        1.extrinsic |   .0080283   .0429361     0.19   0.852    -.0761987    .0922554
                    |
extrinsic#c.concern |
                 1  |  -.1558631   .0630451    -2.47   0.014    -.2795376   -.0321886
                    |
            joinemp |  -.0144498   .0191922    -0.75   0.452    -.0520987    .0231992
            joinpat |  -.0147351     .02152    -0.68   0.494    -.0569506    .0274803
            joincit |  -.0260026   .0244571    -1.06   0.288    -.0739798    .0219745
              ideo6 |  -.0371057   .0235115    -1.58   0.115    -.0832279    .0090165
                rwa |  -.0055373   .0442845    -0.13   0.901    -.0924095    .0813348
                sdo |   .0271871   .0422577     0.64   0.520    -.0557093    .1100834
                 bp |   .1038094   .0326961     3.17   0.002     .0396699    .1679488
           miltherm |   .0532861   .0299229     1.78   0.075    -.0054132    .1119854
               hawk |   .0104462   .0273439     0.38   0.702    -.0431939    .0640863
                age |  -.0093609   .0203285    -0.46   0.645     -.049239    .0305173
                edu |   .0138595   .0179555     0.77   0.440    -.0213634    .0490825
             income |  -.0013613   .0273201    -0.05   0.960    -.0549546    .0522321
           selfserv |  -.0468247   .0282143    -1.66   0.097    -.1021723    .0085228
          household |  -.0039254   .0150289    -0.26   0.794    -.0334075    .0255566
             female |  -.0284531   .0124404    -2.29   0.022    -.0528573    -.004049
              white |   .0035627   .0191542     0.19   0.852    -.0340118    .0411373
              _cons |   .4879084   .0486792    10.02   0.000     .3924152    .5834016
-------------------------------------------------------------------------------------

. estimates store m7d, title(Model 1)

. reg soldierapproval c.persp##extrinsic  joinemp joinpat joincit ideo6  rwa sdo bp miltherm hawk  age  edu income selfserv household female white if control==0

      Source |       SS           df       MS      Number of obs   =     1,400
-------------+----------------------------------   F(19, 1380)     =      5.54
       Model |  4.82564583        19  .253981359   Prob > F        =    0.0000
    Residual |  63.2114524     1,380    .0458054   R-squared       =    0.0709
-------------+----------------------------------   Adj R-squared   =    0.0581
       Total |  68.0370982     1,399  .048632665   Root MSE        =    .21402

-----------------------------------------------------------------------------------
  soldierapproval | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
------------------+----------------------------------------------------------------
            persp |   .1388491   .0517031     2.69   0.007     .0374239    .2402742
      1.extrinsic |   .0100983   .0476729     0.21   0.832     -.083421    .1036176
                  |
extrinsic#c.persp |
               1  |   -.166056   .0731394    -2.27   0.023    -.3095323   -.0225796
                  |
          joinemp |  -.0165939   .0192013    -0.86   0.388    -.0542608    .0210729
          joinpat |  -.0144378   .0215291    -0.67   0.503    -.0566711    .0277955
          joincit |  -.0279342    .024486    -1.14   0.254    -.0759681    .0200996
            ideo6 |  -.0444086   .0233452    -1.90   0.057    -.0902046    .0013874
              rwa |  -.0050318   .0443674    -0.11   0.910    -.0920666    .0820031
              sdo |   .0310178   .0423633     0.73   0.464    -.0520856    .1141213
               bp |   .0968114   .0328346     2.95   0.003     .0324002    .1612226
         miltherm |   .0605908   .0297215     2.04   0.042     .0022866     .118895
             hawk |   .0022672   .0271094     0.08   0.933    -.0509129    .0554473
              age |  -.0047904   .0203199    -0.24   0.814    -.0446516    .0350708
              edu |   .0097425   .0180235     0.54   0.589    -.0256139    .0450989
           income |  -.0024056   .0273623    -0.09   0.930    -.0560818    .0512706
         selfserv |  -.0467262   .0282522    -1.65   0.098    -.1021481    .0086957
        household |  -.0031447   .0150594    -0.21   0.835    -.0326865    .0263971
           female |  -.0236099   .0121586    -1.94   0.052    -.0474613    .0002415
            white |   .0024601   .0191768     0.13   0.898    -.0351587    .0400789
            _cons |   .5081716   .0493667    10.29   0.000     .4113297    .6050135
-----------------------------------------------------------------------------------

. estimates store m8d, title(Model 1)

. 
. esttab m1d m2d m3d m4d m5d m6d m7d m8d using "DoSoldiersGetASay_Table 3.rtf", se r2  replace starlevels(+ 0.10 * 0.05 ** 0.01 *** 0.0001) b(2) se(2)
(file DoSoldiersGetASay_Table 3.rtf not found)
(output written to DoSoldiersGetASay_Table 3.rtf)

. 
. 
. 
. 
. ********************************************************************************
. /// Figure 2: Respondent Belief in Soldier Support for Military Operation ///
> ********************************************************************************
. 
. * Israel
. use "C:\Users\ralstonr\OneDrive - University of Birmingham\Work with Ron\Crossnational Main\Israel.dta"

. reg soldierapproval  intrinsic extrinsic

      Source |       SS           df       MS      Number of obs   =     1,624
-------------+----------------------------------   F(2, 1621)      =     41.24
       Model |  3.45136404         2  1.72568202   Prob > F        =    0.0000
    Residual |  67.8335805     1,621  .041846749   R-squared       =    0.0484
-------------+----------------------------------   Adj R-squared   =    0.0472
       Total |  71.2849446     1,623  .043921716   Root MSE        =    .20456

------------------------------------------------------------------------------
soldierapp~l | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   intrinsic |   .0225782   .0124437     1.81   0.070    -.0018291    .0469856
   extrinsic |  -.0844485   .0124322    -6.79   0.000    -.1088334   -.0600636
       _cons |   .7851852   .0088031    89.19   0.000     .7679186    .8024518
------------------------------------------------------------------------------

. estimates store Israel, title(Model 1)

. 
. * France 
. use "C:\Users\ralstonr\OneDrive - University of Birmingham\Work with Ron\Crossnational Main\France.dta"

. reg soldierapproval intrinsic extrinsic

      Source |       SS           df       MS      Number of obs   =     1,089
-------------+----------------------------------   F(2, 1086)      =     12.04
       Model |  1.36601608         2   .68300804   Prob > F        =    0.0000
    Residual |  61.5962199     1,086  .056718435   R-squared       =    0.0217
-------------+----------------------------------   Adj R-squared   =    0.0199
       Total |   62.962236     1,088  .057869702   Root MSE        =    .23816

------------------------------------------------------------------------------
soldierapp~l | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   intrinsic |   .0652895   .0196957     3.31   0.001     .0266436    .1039354
   extrinsic |  -.0097034   .0198244    -0.49   0.625    -.0486018     .029195
       _cons |   .5951835     .01613    36.90   0.000      .563534    .6268329
------------------------------------------------------------------------------

. estimates store France, title(Model 1)

. 
. * UK
. use "C:\Users\ralstonr\OneDrive - University of Birmingham\Work with Ron\Crossnational Main\UK.dta"

. reg soldierapproval intrinsic extrinsic

      Source |       SS           df       MS      Number of obs   =     2,448
-------------+----------------------------------   F(2, 2445)      =     36.26
       Model |  3.29422214         2  1.64711107   Prob > F        =    0.0000
    Residual |  111.073399     2,445  .045428793   R-squared       =    0.0288
-------------+----------------------------------   Adj R-squared   =    0.0280
       Total |  114.367622     2,447  .046737892   Root MSE        =    .21314

------------------------------------------------------------------------------
soldierapp~l | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   intrinsic |   .0592765   .0103776     5.71   0.000     .0389267    .0796264
   extrinsic |   -.036507   .0104311    -3.50   0.000    -.0569617   -.0160524
       _cons |   .5887405   .0065839    89.42   0.000     .5758298    .6016511
------------------------------------------------------------------------------

. estimates store UK, title(Model 1)

. 
. 
. * USA
. use "C:\Users\ralstonr\OneDrive - University of Birmingham\Work with Ron\Crossnational Main\US.dta"

. reg soldierapproval intrinsic extrinsic

      Source |       SS           df       MS      Number of obs   =     2,451
-------------+----------------------------------   F(2, 2448)      =     87.39
       Model |  11.1685805         2  5.58429027   Prob > F        =    0.0000
    Residual |  156.433011     2,448  .063902374   R-squared       =    0.0666
-------------+----------------------------------   Adj R-squared   =    0.0659
       Total |  167.601591     2,450  .068408813   Root MSE        =    .25279

------------------------------------------------------------------------------
soldierapp~l | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   intrinsic |   .1189398   .0124125     9.58   0.000     .0945998    .1432798
   extrinsic |  -.0552422   .0122542    -4.51   0.000    -.0792719   -.0312124
       _cons |   .6132031    .007805    78.57   0.000      .597898    .6285081
------------------------------------------------------------------------------

. estimates store USA, title(Model 1)

. 
.  
. coefplot Israel France UK USA, scheme(s1mono) mlcolor(black) mfcolor(none) mcolor(black) ///
>                 xline(0, lpattern(dash) lcolor(red%50)) mlabel ///
>                 drop(_cons) mlabposition(6)  ///
>                 aspect(1) xlab(-.5 "Less Favorable"  0  .5 "More Favorable")

. 
. 
. ********************************************************************************
. /// Figure 3: DV Respondent Support for Military Operation—Coefficient Plot ///
> ********************************************************************************
. 
. * France 
. use "C:\Users\ralstonr\OneDrive - University of Birmingham\Work with Ron\Crossnational Main\France.dta",replace

. reg favor soldierapproval intrinsic ideology hawk age selfserv edu income female if control==0 

      Source |       SS           df       MS      Number of obs   =       871
-------------+----------------------------------   F(9, 861)       =      9.61
       Model |  90.9322625         9  10.1035847   Prob > F        =    0.0000
    Residual |  904.996555       861  1.05109937   R-squared       =    0.0913
-------------+----------------------------------   Adj R-squared   =    0.0818
       Total |  995.928817       870  1.14474577   Root MSE        =    1.0252

---------------------------------------------------------------------------------
          favor | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
soldierapproval |    .952436   .1454632     6.55   0.000      .666932     1.23794
      intrinsic |   .0777369   .0706977     1.10   0.272     -.061023    .2164969
       ideology |   .4152311   .1321461     3.14   0.002     .1558648    .6745973
           hawk |   .4703826   .1381454     3.40   0.001     .1992414    .7415237
            age |  -.1366501   .1443972    -0.95   0.344    -.4200619    .1467616
       selfserv |   .2796263   .1017968     2.75   0.006     .0798273    .4794252
            edu |   .0347618   .1364838     0.25   0.799    -.2331181    .3026418
         income |    .153058   .2837793     0.54   0.590    -.4039222    .7100381
         female |  -.0069207   .0771596    -0.09   0.929    -.1583637    .1445223
          _cons |   3.164699    .159601    19.83   0.000     2.851446    3.477951
---------------------------------------------------------------------------------

. estimates store A1, title(Model 1) 

. 
. * Israel
. use "C:\Users\ralstonr\OneDrive - University of Birmingham\Work with Ron\Crossnational Main\Israel.dta", replace

. reg favor soldierapproval intrinsic ideology hawk  age  selfserv edu income female if control==0 

      Source |       SS           df       MS      Number of obs   =     1,003
-------------+----------------------------------   F(9, 993)       =     26.26
       Model |   222.71584         9  24.7462044   Prob > F        =    0.0000
    Residual |  935.621149       993  .942216666   R-squared       =    0.1923
-------------+----------------------------------   Adj R-squared   =    0.1850
       Total |  1158.33699     1,002  1.15602494   Root MSE        =    .97068

---------------------------------------------------------------------------------
          favor | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
soldierapproval |   1.305949   .1593779     8.19   0.000     .9931932    1.618706
      intrinsic |   .0804795   .0638513     1.26   0.208    -.0448194    .2057784
       ideology |   .9383507   .1232022     7.62   0.000     .6965842    1.180117
           hawk |   .4590528   .1338341     3.43   0.001     .1964226    .7216829
            age |   .5188146   .1110115     4.67   0.000     .3009705    .7366587
       selfserv |   .2502408   .0891738     2.81   0.005     .0752501    .4252314
            edu |  -.0100172    .129848    -0.08   0.939    -.2648252    .2447908
         income |   .0935786   .1290528     0.73   0.469    -.1596689    .3468261
         female |  -.1044056   .0633238    -1.65   0.100    -.2286695    .0198582
          _cons |   3.449115    .201372    17.13   0.000     3.053951    3.844278
---------------------------------------------------------------------------------

. estimates store A2, title(Model 1)

. 
. * UK
. use "C:\Users\ralstonr\OneDrive - University of Birmingham\Work with Ron\Crossnational Main\UK.dta", replace

. reg favor soldierapproval intrinsic ideology hawk  age  selfserv edu income female if control==0 

      Source |       SS           df       MS      Number of obs   =     1,400
-------------+----------------------------------   F(9, 1390)      =     22.36
       Model |  271.887015         9  30.2096683   Prob > F        =    0.0000
    Residual |  1877.95227     1,390   1.3510448   R-squared       =    0.1265
-------------+----------------------------------   Adj R-squared   =    0.1208
       Total |  2149.83929     1,399  1.53669713   Root MSE        =    1.1623

---------------------------------------------------------------------------------
          favor | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
soldierapproval |   .8825094   .1446372     6.10   0.000     .5987787     1.16624
      intrinsic |  -.0700946   .0638275    -1.10   0.272    -.1953031     .055114
       ideology |   .7683408   .1341378     5.73   0.000     .5052063    1.031475
           hawk |   1.142002   .1375118     8.30   0.000     .8722488    1.411755
            age |    .332212   .1033396     3.21   0.001     .1294936    .5349304
       selfserv |  -.1755473   .1438226    -1.22   0.222      -.45768    .1065855
            edu |  -.1354463   .0956052    -1.42   0.157    -.3229924    .0520998
         income |   .1382781   .1474475     0.94   0.349    -.1509655    .4275218
         female |  -.1318835   .0645412    -2.04   0.041    -.2584923   -.0052747
          _cons |   2.775718   .1461896    18.99   0.000     2.488942    3.062494
---------------------------------------------------------------------------------

. estimates store A3, title(Model 1)

. 
. * USA
. use "C:\Users\ralstonr\OneDrive - University of Birmingham\Work with Ron\Crossnational Main\US.dta", replace

. reg favor soldierapproval intrinsic ideology hawk  age  selfserv edu income female if control==0 

      Source |       SS           df       MS      Number of obs   =     1,402
-------------+----------------------------------   F(9, 1392)      =     21.46
       Model |  330.029141         9  36.6699046   Prob > F        =    0.0000
    Residual |  2378.19982     1,392  1.70847688   R-squared       =    0.1219
-------------+----------------------------------   Adj R-squared   =    0.1162
       Total |  2708.22896     1,401  1.93306849   Root MSE        =    1.3071

---------------------------------------------------------------------------------
          favor | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
soldierapproval |    1.16864   .1387251     8.42   0.000     .8965071    1.440773
      intrinsic |  -.0163498   .0739866    -0.22   0.825     -.161487    .1287873
       ideology |   .5131282   .1315576     3.90   0.000     .2550557    .7712007
           hawk |   .9889957   .1382006     7.16   0.000     .7178917      1.2601
            age |   .3964277   .1128183     3.51   0.000     .1751155    .6177399
       selfserv |   .1247458   .1108739     1.13   0.261    -.0927521    .3422438
            edu |  -.0646305   .1620288    -0.40   0.690    -.3824774    .2532165
         income |   .2570873   .1666872     1.54   0.123    -.0698979    .5840725
         female |  -.0354673   .0727439    -0.49   0.626    -.1781668    .1072322
          _cons |   2.935088   .1622838    18.09   0.000     2.616741    3.253435
---------------------------------------------------------------------------------

. estimates store A4, title(Model 1)

. 
. coefplot A1 A2 A3 A4,  scheme(s1mono) mlcolor(black) mfcolor(none) mcolor(black) ///
>                 xline(0, lpattern(dash) lcolor(red%50))  ///
>                  drop (_cons) mlabposition(6)  ///
>                 aspect(1) xlab(-2 "Less Operation Support"  0  2.0 "More Operation Support")

. 
. 
. ********************************************************************************
. /// Figure 4: Predicted Probability of Respondent Supporting the Operation
> /// Across Respondent Perception of Soldier Support for Operation ///
> ********************************************************************************
. 
. 
. 
. // Predicted Probabilities - Soldier Approval 
. 
. 
. * France 
. use "C:\Users\ralstonr\OneDrive - University of Birmingham\Work with Ron\Crossnational Main\France.dta"

. 
. logit binaryfavor i.soldierapprovalINT citizen patriot employee desp

Iteration 0:  Log likelihood = -334.73195  
Iteration 1:  Log likelihood = -309.60984  
Iteration 2:  Log likelihood = -309.29371  
Iteration 3:  Log likelihood = -309.29337  
Iteration 4:  Log likelihood = -309.29337  

Logistic regression                                     Number of obs =    542
                                                        LR chi2(8)    =  50.88
                                                        Prob > chi2   = 0.0000
Log likelihood = -309.29337                             Pseudo R2     = 0.0760

------------------------------------------------------------------------------------
       binaryfavor | Coefficient  Std. err.      z    P>|z|     [95% conf. interval]
-------------------+----------------------------------------------------------------
soldierapprovalINT |
                1  |   1.884856   .6511732     2.89   0.004     .6085794    3.161132
                2  |   1.606197   .6075105     2.64   0.008     .4154978    2.796895
                3  |   2.422947    .614931     3.94   0.000     1.217705     3.62819
                4  |   2.638117   .6324163     4.17   0.000     1.398603     3.87763
                   |
           citizen |   .6020215   .3125563     1.93   0.054    -.0105776    1.214621
           patriot |   .3063372    .295383     1.04   0.300    -.2726029    .8852774
          employee |  -.3153683   .2956243    -1.07   0.286    -.8947813    .2640447
              desp |   .8274665   .3298229     2.51   0.012     .1810255    1.473907
             _cons |  -1.487474   .6165722    -2.41   0.016    -2.695933   -.2790146
------------------------------------------------------------------------------------

. margins soldierapprovalINT

Predictive margins                                         Number of obs = 542
Model VCE: OIM

Expression: Pr(binaryfavor), predict()

------------------------------------------------------------------------------------
                   |            Delta-method
                   |     Margin   std. err.      z    P>|z|     [95% conf. interval]
-------------------+----------------------------------------------------------------
soldierapprovalINT |
                0  |   .2391011   .1036442     2.31   0.021     .0359622      .44224
                1  |   .6597542   .0614652    10.73   0.000     .5392846    .7802239
                2  |   .5971157   .0366086    16.31   0.000     .5253641    .6688673
                3  |   .7655591   .0316955    24.15   0.000      .703437    .8276811
                4  |   .8010512   .0366719    21.84   0.000     .7291757    .8729267
------------------------------------------------------------------------------------

. marginsplot, name(France)

Variables that uniquely identify margins: soldierapprovalINT

. 
. * Israel
. use "C:\Users\ralstonr\OneDrive - University of Birmingham\Work with Ron\Crossnational Main\Israel.dta"

. 
. 
. logit binaryfavor i.soldierapprovalINT citizen  employee 

Iteration 0:  Log likelihood = -189.54301  
Iteration 1:  Log likelihood = -183.79329  
Iteration 2:  Log likelihood = -178.94563  
Iteration 3:  Log likelihood = -178.90861  
Iteration 4:  Log likelihood = -178.90858  
Iteration 5:  Log likelihood = -178.90858  

Logistic regression                                     Number of obs =  1,430
                                                        LR chi2(6)    =  21.27
                                                        Prob > chi2   = 0.0016
Log likelihood = -178.90858                             Pseudo R2     = 0.0561

------------------------------------------------------------------------------------
       binaryfavor | Coefficient  Std. err.      z    P>|z|     [95% conf. interval]
-------------------+----------------------------------------------------------------
soldierapprovalINT |
                1  |   .7822642   .8758533     0.89   0.372    -.9343768    2.498905
                2  |   2.061793   .7589543     2.72   0.007     .5742699    3.549316
                3  |   2.699565   .7320539     3.69   0.000     1.264766    4.134365
                4  |   2.953944   .7550668     3.91   0.000      1.47404    4.433847
                   |
           citizen |  -.2065899   .3679801    -0.56   0.575    -.9278176    .5146378
          employee |   .4992094   .4273433     1.17   0.243     -.338368    1.336787
             _cons |   .9593899    .696374     1.38   0.168     -.405478    2.324258
------------------------------------------------------------------------------------

. margins soldierapprovalINT 

Predictive margins                                       Number of obs = 1,430
Model VCE: OIM

Expression: Pr(binaryfavor), predict()

------------------------------------------------------------------------------------
                   |            Delta-method
                   |     Margin   std. err.      z    P>|z|     [95% conf. interval]
-------------------+----------------------------------------------------------------
soldierapprovalINT |
                0  |   .7367241   .1306185     5.64   0.000     .4807166    .9927316
                1  |   .8583665   .0653776    13.13   0.000     .7302288    .9865042
                2  |   .9558088   .0138121    69.20   0.000     .9287376      .98288
                3  |   .9761148   .0060902   160.28   0.000     .9641783    .9880513
                4  |   .9813726   .0058706   167.17   0.000     .9698665    .9928787
------------------------------------------------------------------------------------

. marginsplot, name(Israel)

Variables that uniquely identify margins: soldierapprovalINT

. 
. * UK
. use "C:\Users\ralstonr\OneDrive - University of Birmingham\Work with Ron\Crossnational Main\UK.dta"

. 
. logit binaryfavor i.soldierapprovalINT citizen patriot employee desperate

Iteration 0:  Log likelihood = -948.14077  
Iteration 1:  Log likelihood = -923.60876  
Iteration 2:  Log likelihood = -923.52621  
Iteration 3:  Log likelihood = -923.52621  

Logistic regression                                     Number of obs =  1,437
                                                        LR chi2(8)    =  49.23
                                                        Prob > chi2   = 0.0000
Log likelihood = -923.52621                             Pseudo R2     = 0.0260

------------------------------------------------------------------------------------
       binaryfavor | Coefficient  Std. err.      z    P>|z|     [95% conf. interval]
-------------------+----------------------------------------------------------------
soldierapprovalINT |
                1  |   .0716195   .3695783     0.19   0.846    -.6527406    .7959796
                2  |   .6124508   .3495574     1.75   0.080    -.0726692    1.297571
                3  |   .9332775   .3490268     2.67   0.007     .2491976    1.617357
                4  |    1.24778   .3838081     3.25   0.001     .4955299     2.00003
                   |
           citizen |  -.3997599   .1700232    -2.35   0.019    -.7329993   -.0665205
           patriot |   .0808402   .1782828     0.45   0.650    -.2685877    .4302682
          employee |   .0853482   .1729966     0.49   0.622    -.2537189    .4244154
         desperate |   -.184998   .1702071    -1.09   0.277    -.5185978    .1486019
             _cons |  -.1369492   .3425226    -0.40   0.689    -.8082811    .5343827
------------------------------------------------------------------------------------

. margins soldierapprovalINT

Predictive margins                                       Number of obs = 1,437
Model VCE: OIM

Expression: Pr(binaryfavor), predict()

------------------------------------------------------------------------------------
                   |            Delta-method
                   |     Margin   std. err.      z    P>|z|     [95% conf. interval]
-------------------+----------------------------------------------------------------
soldierapprovalINT |
                0  |   .4524786   .0830235     5.45   0.000     .2897555    .6152018
                1  |   .4701683   .0383182    12.27   0.000      .395066    .5452706
                2  |   .6030181   .0222948    27.05   0.000     .5593211     .646715
                3  |   .6763355    .019456    34.76   0.000     .6382023    .7144686
                4  |   .7407302   .0346619    21.37   0.000      .672794    .8086663
------------------------------------------------------------------------------------

. marginsplot, name(UK)

Variables that uniquely identify margins: soldierapprovalINT

. 
. * USA
. use "C:\Users\ralstonr\OneDrive - University of Birmingham\Work with Ron\Crossnational Main\US.dta"

. 
. logit binaryfavor i.soldierapprovalINT citizen patriot employee desperate

Iteration 0:  Log likelihood = -967.14426  
Iteration 1:  Log likelihood = -939.47188  
Iteration 2:  Log likelihood = -938.86047  
Iteration 3:  Log likelihood = -938.86037  
Iteration 4:  Log likelihood = -938.86037  

Logistic regression                                     Number of obs =  1,687
                                                        LR chi2(8)    =  56.57
                                                        Prob > chi2   = 0.0000
Log likelihood = -938.86037                             Pseudo R2     = 0.0292

------------------------------------------------------------------------------------
       binaryfavor | Coefficient  Std. err.      z    P>|z|     [95% conf. interval]
-------------------+----------------------------------------------------------------
soldierapprovalINT |
                1  |   .5415307   .2964995     1.83   0.068    -.0395976    1.122659
                2  |   1.060817   .2801981     3.79   0.000     .5116385    1.609995
                3  |   1.465829   .2805249     5.23   0.000     .9160102    2.015648
                4  |   1.490151   .2912367     5.12   0.000     .9193376    2.060965
                   |
           citizen |   .0669647    .171151     0.39   0.696    -.2684851    .4024144
           patriot |   .2092947   .1841454     1.14   0.256    -.1516237    .5702131
          employee |    .278184   .1751222     1.59   0.112    -.0650493    .6214172
         desperate |   .1955812   .1799905     1.09   0.277    -.1571936    .5483561
             _cons |  -.2299537   .2696564    -0.85   0.394    -.7584705    .2985631
------------------------------------------------------------------------------------

. margins soldierapprovalINT

Predictive margins                                       Number of obs = 1,687
Model VCE: OIM

Expression: Pr(binaryfavor), predict()

------------------------------------------------------------------------------------
                   |            Delta-method
                   |     Margin   std. err.      z    P>|z|     [95% conf. interval]
-------------------+----------------------------------------------------------------
soldierapprovalINT |
                0  |   .4688606   .0645486     7.26   0.000     .3423477    .5953736
                1  |   .6023404   .0356961    16.87   0.000     .5323774    .6723034
                2  |   .7177153   .0214549    33.45   0.000     .6756645    .7597661
                3  |   .7920461   .0168498    47.01   0.000     .7590211     .825071
                4  |   .7960162   .0204393    38.95   0.000      .755956    .8360764
------------------------------------------------------------------------------------

. marginsplot, name(US)

Variables that uniquely identify margins: soldierapprovalINT

. 
. graph combine US France Israel UK, name(combined_plot_pop)

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end of do-file

. log close
      name:  <unnamed>
       log:  C:\Users\ralstonr\OneDrive - University of Birmingham\Work with Ron\Crossnational Main\Do Soldiers Get a Say.log
  log type:  text
 closed on:   8 Oct 2024, 09:25:49
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------
